You have two datasets to merge. One lists a company as "Apple Inc." The other lists "Apple Incorporated." You try a standard SQL JOIN or Pandas merge, and......
Natural Language Processing (NLP) is messy. While human brains effortlessly process sarcasm, emojis, and slang, computers see nothing but a stream of meaning...
If you ask a data scientist what keeps them up at night, it isn't gradient descent or hyperparameter tuning—it's date parsing.
Data scientists famously spend 80% of their time cleaning data and only 20% analyzing it. While this statistic is often cited as a complaint, seasoned profes...
Imagine you are building a model to predict house prices, and your dataset contains a "Zip Code" column. In the United States alone, there are over 40,000 un...
You have cleaned your data, handled missing values, and you are ready to train your first model. You run and immediately hit a brick wall: .
Imagine building a predictive model for a bank loan system. You have income data for 90% of applicants, but for the other 10%, the field is empty. If you sim...
You can have the most sophisticated algorithm in the world—a deep neural network with millions of parameters—but if you feed the network raw, unprocessed gar...
